POS0379 WHEN SHOULD WE USE MARGINAL STRUCTURAL MODELS FOR DRUG STUDIES IN RHEUMATOLOGY? THE EXAMPLE OF CORTICOSTEROIDS AND INFECTIONS IN RHEUMATOID ARTHRITIS
Authors: A. Barbulescu, A. Sjölander, B. Delcoigne, J. Askling, T. Frisell
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> The use and dosing of pharmacotherapy for chronic inflammatory disease is commonly changed over time, adapting to previous treatment response, current disease activity, tolerability, and onset of adverse events. This makes evaluating the treatments difficult, as the treatment received over time becomes entangled with time-varying confounding factors, even if the initial treatment choice was randomized. To naïvely adjust for these time-varying factors in regression models have long been recognized by epidemiologists to introduce bias in most realistic settings, and marginal structural models (MSM) has been proposed as a less biased alternative. Despite this, MSMs are used very sparingly in drug studies in rheumatology. <h3>Objectives</h3> The objective of this work is to explain the rationale for why MSMs are recommended in the context of time-varying drug use and confounding factors, and what may go wrong if they are not used. The method will be demonstrated by comparing the incidence of serious infections between different oral glucocorticoid (GC) dose patterns over the first three years after first RA diagnosis, adjusting for time-varying confounders in MSM or through conventional regression models. <h3>Methods</h3> For the demonstration study, we followed 9654 recently diagnosed RA patients for three years from their first rheumatology visit in the Swedish rheumatology register (SRQ), 2007 to 2018. Follow-up was divided into 3-month periods. An average oral prednisone daily-dose was calculated for each period and categorized into "no use", "low" (≤10mg/day) and "high" (&gt;10mg/day) doses. The MSM was implemented through sequential inverse probability of treatment weighting across time periods, accounting for demographic factors, current DAS28 and HAQ, co-medication and history of comorbidity. The incidence of serious infections (hospitalization for infection identified through the Swedish National Patient Register) was modelled by pooled logistic regression allowing separate effects for recent and past GC. We compared confounding adjustment via conventional regression versus MSM. <h3>Results</h3> An increased incidence of serious infections was associated with higher compared to lower doses and with more recent compared to past GC. Although in theory less biased by confounding factors, the results from MSMs were similar to those from conventional regression. Compared to no glucocorticoids, exposure to low doses during the first year added 1.9 infection cases per 100 patients (95%CI 0.9-2.9) at three years, while exposure to high doses added 4.1 (2.5-5.9) cases. <h3>Conclusion</h3> Our results broadly agree with previous observational studies showing a dose dependent increased risk of infection associated with (recent) use of oral glucocorticoids. Although theoretically the MSM has the potential to be less biased than ordinary regression models, the results from the two models were almost indistinguishable in this realistic example, and the implementation of the MSM led to limitations in the study design (including the categorization of exposure), and was very time consuming both in programming and computation time compared to the more widely used option. This similarity in results is not guaranteed however, and the biases that MSMs were designed to avoid should be kept in mind in all studies of drugs were the use may change over time in response to possibly confounding factors. <h3>REFERENCES:</h3> NIL. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> Andrei Barbulescu Consultant of: Employee of Parexel, Arvid Sjölander: None declared, Bénédicte Delcoigne: None declared, Johan Askling Grant/research support from: JA is PI of the ARTIS project, which is supported by agreements between Karolinska Institutet and the listed entities, mainly for the national safety monitoring of rheumatology immunomodulators in Sweden (ARTIS): Abbvie, BMS, Eli Lilly, Galapagos, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi., Thomas Frisell: None declared.